InsightX Suite

InsightX is the advanced industrial analytics and intelligence suite within the IngeneroX ecosystem. It transforms operational and engineering data into deeper insights that help teams detect process deviations, evaluate control performance, develop predictive models, and deploy engineering algorithms across plant operations.

By bringing together AlertX, APCperformX, AnalyticX, and AlgoX, InsightX combines process-aware detection, advanced process control performance monitoring, no-code analytics, and engineering model deployment within a connected environment. It enables organizations to move beyond basic monitoring toward deeper diagnosis, prediction, and actionable industrial intelligence.

Salient Features

Process Deviation Detection & Diagnosis

Continuously identify abnormal process behavior, prioritize meaningful deviations, and provide diagnostic context to help teams understand potential causes and required actions.

Advanced Control Performance Intelligence

Monitor APC and DMC performance, controller health, operating constraints, and variable behavior to identify factors limiting control effectiveness and optimization.

No-Code Predictive Analytics

Enable engineers to explore operational data and build, validate, and deploy machine learning and time-series forecasting models through a no-code analytics environment.

Engineering Model & Algorithm Deployment

Integrate and operationalize existing engineering calculations, custom algorithms, and legacy models by connecting them directly with plant data in a governed environment.

Customizable Limits, Priorities, etc.

a. Engineers can manipulate configured KPI limits based on plant priorities.

Sensitivity Analysis

Optimax provides feature to run multiple cases simultaneously with different limit ranges to enhance the actionable insights.

Role-Based Access and Security

Provides access control to ensure only authorized personnel can view or edit monitoring configurations.

Result Analysis Tool

Offers diagnostic tools to help engineers quickly investigate and resolve performance issues with different configurations

Client Benefits

Identify Operational Issues Earlier

Detect meaningful process deviations and abnormal behavior earlier, giving engineering and operations teams more time to investigate and respond.

Accelerate Root-Cause Analysis

Combine process-aware detection and advanced analytics to help engineers investigate deviations and identify contributing factors more efficiently.

Maximize Existing Engineering & APC Investments

Extend the value of existing APC applications, engineering models, calculations, and legacy algorithms by continuously monitoring and operationalizing them.

Reduce Dependence on Specialized Resources

Enable process engineers to perform advanced analysis and develop predictive models without requiring extensive coding or continuous dependence on data science teams.

Dashboard & Snapshots

Configure all tags related to specific Equipment:

Solution configuration [Defining the Objective: Maximize Production, Minimize Utility]:

Solution configuration [Defining cases of interest – Multiple cases can also be added]:

Result Tag Configuration: Identify the potential actionable insights.

Sensitivity Analysis: Supporting engineers to evaluate appropriate configurations

Case Studies

Development of Soft Sensor to predict the C5 contents in Debutaniser column Overhead:

Background

In modern petrochemical operations, maintaining product specifications within tight limits is critical for both quality assurance and process efficiency. One of the key challenges faced by a leading chemical plant was the need for real-time prediction and monitoring of C5 content in the overhead stream of the debutanizer column — a crucial step to ensure product specification compliance and optimize operations.

Challenge

Traditional laboratory testing methods for measuring C5 content introduced significant time delays, making real-time adjustments difficult. The plant required a fast, accurate, and reliable solution to continuously monitor C5 levels, allowing operators to take timely corrective actions and avoid off-spec products.

Solution with AnalyticX

Using AnalyticX, the engineering team was able to develop a soft sensor — a machine learning-based predictive model — specifically designed to estimate the C5 content in the debutanizer overhead stream in real time.

Key steps included:

Seamless ingestion of historical operational data into AnalyticX without any coding requirements.
Applying statistical analysis to identify key process variables influencing C5 concentrations.
Rapid development and training of a machine learning model tailored to predict C5 content with high accuracy.
Deployment of the predictive model into live operations for real-time product spec monitoring.

Results

Enhanced Product Monitoring:
Operators now have a real-time view of the predicted C5 content, significantly reducing reliance on delayed lab measurements.
Improved Process Control:
By closely tracking C5 levels, the plant was able to make timely adjustments to operational parameters, ensuring consistent product quality.
Reduced Off-Spec Production:
Real-time insights helped minimize off-spec batches, leading to material savings and reduced reprocessing costs.

Key Takeaways

AnalyticX enabled the rapid development of a soft sensor customized for critical KPI monitoring.

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